Using Discretely Integrated Condition Event Simulation To Construct Quantitative Benefit–Risk Models: The Example of Rotavirus Vaccination in France

• Published in: Clinical therapeutics 2020-10, Vol.42 (10), p.1983-1991.e2
• Main Authors: Arlegui, Hugo, Nachbaur, Gaëlle, Praet, Nicolas, Bégaud, Bernard, Caro, J. Jaime
• Format: Article
• Language: English
• Subjects: Age; benefit-risk model; Decision making; DICE; discretely integrated condition event; Fatalities; Gastroenteritis; Hospitalization; Human health and pathology; Immunization; Immunology; Infectious diseases; Intervention; Intussusception; Life Sciences; Risk assessment; Rotavirus; Santé publique et épidémiologie; Sensitivity analysis; Simulation; simulation method; Spreadsheets; Vaccination; Vaccines; Vaccinology; Viruses
• ISSN: 0149-2918; 1879-114X
• DOI: 10.1016/j.clinthera.2020.08.013

Although quantitative benefit–risk models (qBRms) are indisputably valuable tools for gaining comprehensive assessments of health care interventions, they are not systematically used, probably because they lack an integrated framework that provides methodologic structure and harmonization. An alternative that allows all stakeholders to design operational models starting from a standardized framework was recently developed: the discretely integrated condition event (DICE) simulation. The aim of the present work was to assess the feasibility of implementing a qBRm in DICE, using the example of rotavirus vaccination. A model of rotavirus vaccination was designed using DICE and implemented in spreadsheet software with 3 worksheets: Conditions, Events, and Outputs. Conditions held the information in the model; this information changed at Events, and Outputs were special Conditions that stored the results collected during the analysis. A hypothetical French birth cohort was simulated for the assessment of rotavirus vaccination over time. The benefits were estimated for up to 5 years, and the risks in the 7 days following rotavirus vaccination versus no vaccination were assessed, with the results expressed as benefit–risk ratios. This qBRm model required 8 Events, 38 Conditions, and 9 Outputs. Two Events cyclically updated the rates of rotavirus gastroenteritis (RVGE) and intussusception (IS) according to age. Vaccination occurred at 2 additional Events, according to the vaccination scheme applied in France, and affected the occurrence of the other Events. Outputs were the numbers of hospitalizations related to RVGE and to IS, and related deaths. The entire model was specified in a small set of tables contained in a 445-KB electronic workbook. Analyses showed that for each IS-related hospitalization or death caused, 1613 (95% credible interval, 1001–2800) RVGE-related hospitalizations and 787 (95% credible interval, 246–2691) RVGE-related deaths would be prevented by vaccination. These results are consistent with those from a published French study using similar inputs but a very different modeling approach. A limitation of the DICE approach was the extended run time needed for completing the sensitivity analyses when implemented in the electronic worksheets. DICE provided a user-friendly integrated framework for developing qBRms and should be considered in the development of structured approaches to facilitate benefit–risk assessment. •Quantitative models are cr